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Temporary Machine Learning Scientist Jobs in Newark, NJ

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Stay updated with the latest trends and technologies in data science and machine learning. Basic Qualifications: Proficient in Python, Pandas, NumPy, Scikit-Learn, PySpark Bachelor s degree in ...

Qualcomm

Machine Learning Compiler

Manhattan, NY · On-site

$141 - $211/hr

Master's degree in Computer Science, Engineering, Information Systems, or related field. * 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras ...

Forhyre

Machine Learning Engineer

New York, NY

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

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Temporary Machine Learning Scientist information

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a temporary machine learning scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

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What cities near Newark, NJ are hiring for Temporary Machine Learning Scientist jobs?

Cities near Newark, NJ with the most Temporary Machine Learning Scientist job openings:

Temporary Machine Learning Scientist jobs near you

Deep Learning Scientist - eFinancialCareers

eFinancialCareers

Manhattan, NY • On-site

Full-time

Re-posted 3 days ago

Job description

Company Overview:

We are a distinguished firm known for our leading-edge research and development in the financial sector. With an emphasis on innovation and a collaborative culture, we strive to attract and nurture top-tier talent. Our workplace is crafted to encourage creativity and peak performance. At the heart of our operations is a commitment to a culture defined by collaboration, meritocracy, ambition, and determination—qualities that foster an ambitious and results-oriented atmosphere. Our investment strategies are systematic, supported by a robust research and development platform, with the goal of consistently delivering industry-leading returns.

Vision:

We value specialists who can immediately contribute and enhance our dynamic team with diverse skill sets and backgrounds. The computational models we are developing are becoming increasingly complex, and computational power is paramount.

The Opportunity:

  1. Engage in an evolving environment that champions complexity and growth.
  2. Work at the forefront of machine learning, recognizing and harnessing its transformative potential.
  3. Thrive in a setting that combines the agility of a start-up with the stability of a well-funded entity—a perfect playground for innovation.
  4. Experience mid to long-term growth opportunities, including leading teams and spearheading technology initiatives.

We Are Seeking:

Talented deep learning scientists who are eager to create and refine proprietary trading models and strategies. Our scientists collaborate closely with engineers, researchers, and senior leaders, with the scope to undertake independent research and develop new research themes over time.

Responsibilities Include:

  1. Employing financial and other data sources to construct or enhance predictive models.
  2. Utilizing state-of-the-art statistical and machine-learning models to bolster our R&D system.
  3. Designing algorithms to capitalize on predictive signals.

Technical Qualifications:

  1. Advanced degree (PhD or Postdoc) in finance, computer science, mathematics, statistics, machine learning, physics, or a related scientific discipline.
  2. Strong mathematical, analytical, and problem-solving skills.
  3. Experience conducting high-level statistical or applied mathematical research.
  4. Prior quantitative trading environment experience is advantageous.
  5. Proficiency in programming with C++, Java, or Python.

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